AI-English Language Generated Content: Navigating the Fine Line Between Originality and Plagiarism

محورهای موضوعی : Research in English Language Pedagogy

Masoud Neysani ¹ , Seyedeh Elham Elhambakhsh ² , Ahmadreza Nikbakht ³

1 - Department of English Language and Literature, Yazd University, Yazd, Iran
2 - Department of English Language and Literature, Yazd University, Yazd, Iran
3 - Department of English Language and Literature, Yazd University, Yazd, Iran

تاریخ دریافت : 1402/09/05 تاریخ پذیرش : 1402/11/08 تاریخ انتشار : 1403/03/20

کلید واژه: AI- English language generated content, Creativity, English language teaching, Originality, Plagiarism detection,

چکیده مقاله :

The era of AI-generated content has introduced a profound transformation in the realms of creativity, authorship, and intellectual property rights. This study examined two research aspects. Firstly, it explored the impact of AI- English language-generated content on the traditional boundaries of authorship, creativity, and intellectual property rights. Secondly, it investigated the ethical and legal challenges associated with AI's influence on TEFL content generation and how the academic communities address these concerns. The research team employed a mixed-methods approach. Twenty-Eight individuals, organizations, and professionals made up the target population of the current study. The researchers interviewed experts in the fields of AI, law, and English language material development. The researchers analyzed real-world cases of AI-TEFL generated content usage, particularly within academic settings. The findings revealed that AI-generated content challenges conventional notions of authorship and creativity by introducing autonomous AI creators while also augmenting human creativity. The ambiguous landscape of intellectual property rights necessitates adaptive legal frameworks. While AI challenges established norms, it also offers opportunities for collaboration and inspiration. To address these issues, collaborative frameworks, ethical guidelines, and transparency were proposed as integral solutions. Respondents emphasize collaborative efforts to address the ethical and legal concerns associated with AI's influence on content generation within the academic communities. The implications extend to various sectors, including academia, creative industries, and legal systems. This study underscores the pressing need for a delicate balance between AI's creative potential and the preservation of ethical and legal standards in the evolving landscape of content creation.

چکیده انگلیسی:

The era of AI-generated content has introduced a profound transformation in the realms of creativity, authorship, and intellectual property rights. This study examined two research aspects. Firstly, it explored the impact of AI- English language-generated content on the traditional boundaries of authorship, creativity, and intellectual property rights. Secondly, it investigated the ethical and legal challenges associated with AI's influence on TEFL content generation and how the academic communities address these concerns. The research team employed a mixed-methods approach. Twenty-Eight individuals, organizations, and professionals made up the target population of the current study. The researchers interviewed experts in the fields of AI, law, and English language material development. The researchers analyzed real-world cases of AI-TEFL generated content usage, particularly within academic settings. The findings revealed that AI-generated content challenges conventional notions of authorship and creativity by introducing autonomous AI creators while also augmenting human creativity. The ambiguous landscape of intellectual property rights necessitates adaptive legal frameworks. While AI challenges established norms, it also offers opportunities for collaboration and inspiration. To address these issues, collaborative frameworks, ethical guidelines, and transparency were proposed as integral solutions. Respondents emphasize collaborative efforts to address the ethical and legal concerns associated with AI's influence on content generation within the academic communities. The implications extend to various sectors, including academia, creative industries, and legal systems. This study underscores the pressing need for a delicate balance between AI's creative potential and the preservation of ethical and legal standards in the evolving landscape of content creation.

منابع و مأخذ:

Ary, D., Jacobs, L. C., & Sorensen, C. (2010). Introduction to research in education. Wadsworth: Cengage Learning.
Birunda, S. S. & Devi, R. K. (2021). A review on word embedding techniques for text classification. In J. S. Raj, A. M. Iliyasu, R. Bestak, and Z. A. Baig (Eds.), Innovative Data Communication Technologies and Application, (pp. 267-281). https://doi.org/10.1007/978-981-15-9651-3_23
Boden, M. A. & Edmonds, E. A. (2010). What is genera¬tive art? Digital Creativity, 20(1-2), 21- 46. https://doi. org/10.1080/14626260902867915
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language models are few-shot learners.
https://arxiv.org/ abs/2005.14165.
Chan, A. (2023). GPT-3 & InstructGPT: Technological dystopianism, utopianism, and ‘Contextual’ perspectives in AI ethics and industry. AI and Ethics, 3(1), 53-64. https://doi.org/10.1007/s43681-022-00148-6
Chowdhury, H. A. & Bhattacharyya, D. K. (2018). Plagiarism: Taxonomy, tools and detection techniques. Oxford University Press.
Cortiz, D. (2022). Exploring transformers models for emotion recognition: A comparison of BERT, DistilBERT, RoBERTa, XLNET and ELECTRA. Proceedings of the 2022 3rd International Conference on Control, Robotics and Intelligent System, (pp. 230-234). https://doi. org/10.1145/3562007.3562051
Crothers, E., Japkowicz, N., & Viktor, H. (2023). Machine generated text: A comprehensive survey of threat models and detection methods. Available at: https://arxiv.org/ abs/2210.07321
Dornyei, Z. (2007). Research methods in applied linguistics quantitative, qualitative, and mixed methodologies. Oxford: Oxford University Press. England.
Field, A. (2005). “Discovering Statistics Using SPSS: Introducing Statistical Method (3rd ed.)”. Thousand Oaks, CA: Sage Publications.
Gervais, D. J. (2002). Feist goes global: A comparative analysis of the notion of originality in copyright law. Journal of the Copyright Society of the U.S.A. 49, 949-981. https://ssrn.com/abstract=733603
King, M. R. & chatGPT. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and Molecular Bioengineering, 16(1), 1-2. https://doi.org/10.1007/s12195-022-00754-8
Labbé, C. & Labbé, D. (2013). Duplicate and fake publi¬cations in the scientific literature: How many SCIgen papers in computer science? Scientometrics, 94(1), 379- 396. https://doi.org/10.1007/s11192-012-0781-y
Mackey, A., & Gass, S. M. (2005). Second language research methodology and design. New Jersey: Lawrence Erlbaum Associates.
Oberreuter, G. & Velásquez, J. D. (2013). Text mining applied to plagiarism detection: The use of words for detecting deviations in the writing style-ScienceDirect. Expert Systems with Applications, 40(9), 3756-3763. https://doi.org/10.1016/j.eswa.2012.12.082
O’Connor, S. & ChatGPT. (2023). Open artificial intelli¬gence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice, 66. https://doi.org/10.1016/j.nepr.2022.103537
Oladokun, B. D., Seidu, A. E., Ogunbiyi, J. O., Aboyade, W. A., Yemi-Peters, O. E. & Elai, M. A. (2022). Utilization of Information and Communication Technologies (ICTs) for managing students’ academic records in Nigerian Schools. SRELS Journal of Information Management, (pp. 373-381). https://doi.org/10.17821/ srels/2022/v59i6/168449
Oya, M. (2020). Syntactic similarity of the sentences in a multi-lingual parallel corpus based on the Euclidean dis¬tance of their dependency trees. Proceedings of the 34th Pacific Asia Conference on Language, Information, and Computation, (pp. 225-233).
Pal, A. & Mukhopadhyay, P. (2022). Fetching automatic authority data in ILS from Wikidata via OpenRefine. SRELS Journal of Information Management, (pp. 353-362). https://doi.org/10.17821/srels/2022/v59i6/170677
Parmar, R. D. & Nagi, P. K. (2022). Institutional knowl¬edge repositories: Re-contextualization for accreditation and quality management. SRELS Journal of Information Management, 383-390. https://doi.org/10.17821/ srels/2022/v59i6/170796
Pataranutaporn, P., Danry, V., Leong, J., Punpongsanon, P., Novy, D., Maes, P. and Sra, M. (2021). AI-generated characters for supporting personalized learning and well-being. Nature Machine Intelligence, 3(12). https:// doi.org/10.1038/s42256-021-00417-9
Petroni, F., Rocktäschel, T., Riedel, S., Lewis, P., Bakhtin, A., Wu, Y. and Miller, A. (2019). Language models as knowledge bases? Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2463-2473. https://doi.org/10.18653/v1/D19-1250
Roy, B. K., & Mukhopadhyay, P. (2022). Digital access brokers: Clustering and comparison (Part II - from Summarization to Citation Map). SRELS Journal of Information Management, 337-351. https://doi. org/10.17821/srels/2022/v59i6/170786
Topal, M. O., Bas, A. & van Heerden, I. (2021). Exploring transformers in natural language generation: GPT, BERT, and XLNet. Available at: https://arxiv.org/ abs/2102.08036
Transformer, G. G. P., Thunström, A. O. & Steingrimsson, S. (2022). Can GPT-3 write an academic paper on itself, with minimal human input? Oxford University Press.
van Noorden, R. (2014). Publishers withdraw more than 120 gibberish papers. Nature. https://doi.org/10.1038/ nature.2014.14763
Weizenbaum, J. (1966). ELIZA-a computer program for the study of natural language communication between man and machine. Communications of the ACM, 36-45. https://doi.org/10.1145/365153.365168
Writer, B. (2019). Lithium-ion batteries: A machine-gener¬ated summary of current research. Springer International Publishing. https://doi.org/10.1007/978-3-030-16800-1